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ATOCore/docs/master-plan-status.md
Anto01 e2895b5d2b feat: Phase 8 OpenClaw integration verified end-to-end 
Verified t420-openclaw/atocore.py against live Dalidou from both
the development machine and the T420 (clawdbot @ 192.168.86.39):

- health: returns 0.2.0 + build_sha + vector count
- auto-context: project detection + context/build produces full
  packs with Trusted Project State, Project Memories band, and
  retrieved chunks (tested p05 vendor query and p06 firmware query)
- fail-open: unreachable host returns {status: unavailable,
  fail_open: true} without crashing or blocking the session

API surface coverage: atocore.py hits 15/33 endpoints (core
retrieval + project state + context build). Memory management,
interactions, and backup endpoints are correctly excluded — those
belong to the operator client (scripts/atocore_client.py) per the
read-only additive integration model.

No code changes needed — the April 6 atocore.py already matches
the current API surface. Wave 2 state entries and project-memory
band changes are transparent to the client (they enrich
formatted_context without requiring client-side updates).

Cloned repo to T420 at /home/papa/ATOCore for future OpenClaw use.
Updated master-plan-status.md: Phase 8 moved from Partial to
Baseline Complete.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-12 08:50:51 -04:00

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AtoCore Master Plan Status

Current Position

AtoCore is currently between Phase 7 and Phase 8.

The platform is no longer just a proof of concept. The local engine exists, the core correctness pass is complete, Dalidou hosts the canonical runtime and machine database, and OpenClaw on the T420 can consume AtoCore safely in read-only additive mode.

Phase Status

Completed

  • Phase 0 - Foundation
  • Phase 0.5 - Proof of Concept
  • Phase 1 - Ingestion

Baseline Complete

  • Phase 2 - Memory Core
  • Phase 3 - Retrieval
  • Phase 5 - Project State
  • Phase 7 - Context Builder

Partial

  • Phase 4 - Identity / Preferences

Baseline Complete

  • Phase 8 - OpenClaw Integration. As of 2026-04-12 the T420 OpenClaw helper (t420-openclaw/atocore.py) is verified end-to-end against live Dalidou: health check, auto-context with project detection, Trusted Project State surfacing, project-memory band, fail-open on unreachable host. Tested from both the development machine and the T420 via SSH. The helper covers 15 of the 33 API endpoints — the excluded endpoints (memory management, interactions, backup) are correctly scoped to the operator client (scripts/atocore_client.py) per the read-only additive integration model.

Baseline Complete

  • Phase 9 - Reflection (all three foundation commits landed: A capture, B reinforcement, C candidate extraction + review queue). As of 2026-04-11 the capture → reinforce half runs automatically on every Stop-hook capture (length-aware token-overlap matcher handles paragraph-length memories), and project-scoped memories now reach the context pack via a dedicated --- Project Memories --- band between identity/preference and retrieved chunks. The extract half is still a manual / batch flow by design (scripts/atocore_client.py batch-extract + triage). First live batch-extract run over 42 captured interactions produced 1 candidate (rule extractor is conservative and keys on structural cues like ## Decision: headings that rarely appear in conversational LLM responses) — extractor tuning is a known follow-up.

Not Yet Complete In The Intended Sense

  • Phase 6 - AtoDrive
  • Phase 10 - Write-back
  • Phase 11 - Multi-model
  • Phase 12 - Evaluation
  • Phase 13 - Hardening

Engineering Layer Planning Sprint

Status: complete. All 8 architecture docs are drafted. The engineering layer is now ready for V1 implementation against the active project set.

The next concrete next step is the V1 implementation sprint, which should follow engineering-v1-acceptance.md as its checklist, and must apply the project-identity-canonicalization contract at every new service-layer entry point.

LLM Client Integration

A separate but related architectural concern: how AtoCore is reachable from many different LLM client contexts (OpenClaw, Claude Code, future Codex skills, future MCP server). The layering rule is documented in:

  • llm-client-integration.md — three-layer shape: HTTP API → shared operator client (scripts/atocore_client.py) → per-agent thin frontends; the shared client is the canonical backbone every new client should shell out to instead of reimplementing HTTP calls

This sits implicitly between Phase 8 (OpenClaw) and Phase 11 (multi-model). Memory-review and engineering-entity commands are deferred from the shared client until their workflows are exercised.

What Is Real Today

  • canonical AtoCore runtime on Dalidou
  • canonical machine DB and vector store on Dalidou
  • project registry with:
    • template
    • proposal preview
    • register
    • update
    • refresh
  • read-only additive OpenClaw helper on the T420
  • seeded project corpus for:
    • p04-gigabit
    • p05-interferometer
    • p06-polisher
  • conservative Trusted Project State for those active projects
  • first operational backup foundation for SQLite + project registry
  • implementation-facing architecture notes for future engineering knowledge work
  • first organic routing layer in OpenClaw via:
    • detect-project
    • auto-context

Now

These are the current practical priorities.

  1. Finish practical OpenClaw integration
    • make the helper lifecycle feel natural in daily use
    • use the new organic routing layer for project-knowledge questions
    • confirm fail-open behavior remains acceptable
    • keep AtoCore clearly additive
  2. Tighten retrieval quality
    • reduce cross-project competition
    • improve ranking on short or ambiguous prompts
    • add only a few anchor docs where retrieval is still weak
  3. Continue controlled ingestion
    • deepen active projects selectively
    • avoid noisy bulk corpus growth
  4. Strengthen operational boringness
    • backup and restore procedure
    • Chroma rebuild / backup policy
    • retention and restore validation

Next

These are the next major layers after the current practical pass.

  1. Clarify AtoDrive as a real operational truth layer
  2. Mature identity / preferences handling
  3. Improve observability for:
    • retrieval quality
    • context-pack inspection
    • comparison of behavior with and without AtoCore

Later

These are the deliberate future expansions already supported by the architecture direction, but not yet ready for immediate implementation.

  1. Minimal engineering knowledge layer
    • driven by docs/architecture/engineering-knowledge-hybrid-architecture.md
    • guided by docs/architecture/engineering-ontology-v1.md
  2. Minimal typed objects and relationships
  3. Evidence-linking and provenance-rich structured records
  4. Human mirror generation from structured state

Not Yet

These remain intentionally deferred.

  • automatic write-back from OpenClaw into AtoCore
  • automatic memory promotion
  • reflection loop integration — baseline now in (capture→reinforce auto, extract batch/manual). Extractor tuning and scheduled batch extraction still open.
  • replacing OpenClaw's own memory system
  • live machine-DB sync between machines
  • full ontology / graph expansion before the current baseline is stable

Working Rule

The next sensible implementation threshold for the engineering ontology work is:

  • after the current ingestion, retrieval, registry, OpenClaw helper, organic routing, and backup baseline feels boring and dependable

Until then, the architecture docs should shape decisions, not force premature schema work.

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